How To Use Dynamic Data Visualization To Present Data Better

Because data is important to individuals and businesses alike, it is crucial to know when and how to monitor it. When data changes constantly, regular progress assessments become critical. One way to evaluate progress is through visualizations.

According to the data depicted, you can choose a dynamic or static representation. Dynamic data visualization offers a better experience because it is interactive and comprehensive.

This article will focus on visualization types and explain their advantages. It will also describe seven examples of dynamic representations. But first, consider what dynamic visualizations are and how they differ from static ones.

Dynamic Data Visualization – What is it?

Static vs. Dynamic Visualization

Data visualizations display your choices regarding four variables: access, processing, representation, and interaction. When visualizing a map or chart, you aim to locate the correlation points between the graphic and its data.

When the chart is static, you yourself must identify these match points. In a dynamic map, they become moving objects.

Static data visualizations are easier to decode because they capture a single moment of information. Contrarily, dynamic charts display many data moments. Thus, they demand that users create filtering variables and processing alternatives.

Still, the most significant difference between these visualizations is their ability to adjust.

What are dynamic charts?

Dynamic charts are tools that display the latest data using interactive resources. They improve visualization and analysis.

These graphs are not dynamic because of motion effects, but because they are based on flexible templates. They constantly adapt to data changes and selected variables, so they do not respond to a fixed layout.

This way, users can visualize and identify patterns that match current trends. Unlike other static charts, dynamic visualizations are highly interactive. Hence, the attributes of the objects displayed are also adjustable.

Interactive vs. Linear Dynamic Visualizations

There are two types of dynamic data visualization: interactive and linear. You can choose between these types based on the data presented and your purpose for the map.

Interactive charts enable users to determine their preferred presentation configurations. They can introduce dynamic features during the visualization process or throughout the analysis.

For example, an interactive dynamic visualization might include animations. It can display customizing options and live-streaming data.

Linear visualizations adjust automatically and do not allow for further alterations. Non-interactive animations are an example of linear data visualizations.

Your beautiful data deserves to be online

wpDataTables can make it that way. There’s a good reason why it’s the #1 WordPress plugin for creating responsive tables and charts.

An actual example of wpDataTables in the wild

And it’s really easy to do something like this:

You provide the table data
Configure and customize it
Publish it in a post or page

And it’s not just pretty, but also practical. You can make large tables with up to millions of rows, or you can use advanced filters and search, or you can go wild and make it editable.

“Yeah, but I just like Excel too much and there’s nothing like that on websites”. Yeah, there is. You can use conditional formatting like in Excel or Google Sheets.

Did I tell you you can create charts too with your data? And that’s only a small part. There are lots of other features for you.

The Advantages of Dynamic Visualizations

Access to Real-time Data

Static visualization becomes permanently outdated as information changes. A dynamic graphic processes current data as it changes.

It allows decision-makers to visualize and explore up-to-date information. Which‌ will enable them to provide more efficient guidance.

Facilitated Identification of Trends

Visual data is much less demanding to interpret and analyze for the human brain. Thus, dynamic data visualizations allow business leaders to identify current patterns and trends.

They can understand data relationships and act accordingly.

Simplified Understanding of Complex Data

An interactive map permits a broad simplification of datasets, no matter how large or complex. Introducing tools to enable dynamic visualizing adds value and assists a correct analysis.

Make Fast and Precise Decisions

One of the most significant advantages of interactive visualization is faster decision-making.. The data presented in these graphs is always precise and up to date.

Businesses can use these graphs and make impactful decisions according to current needs and events.

Common Examples of Dynamic Data Visualizations

Demographic Dynamic Visualization Maps

Map by Location

Here you can access a video map to display the evolution of the population in major American cities from 1790 to 2010. The circles that point out the growth of each population center are easy to understand.

The linked example shows how presenting dynamic visualizations surpasses simple graphs.

Map by Region

This second example is a choropleth map that shows data related to crime rates in the United States between 1965 and 2010. It is a video presentation that allows you to identify the values of each state.

The Population Pyramid

The population pyramid is one of the most common demographic diagrams. It is a presentation of the distribution of a population according to gender and age. Thus, it is valuable for governments to monitor population numbers.

The next example contains a collection of bar graphs representing the American population pyramids from 1950 to 2012. This dynamic visualization allows for various types of readings, individually or as a set.

Geographic Dynamic Visualization

Wind Roses

Wind roses are valuable graphic tools to display wind conditions, speed, and direction. They encompass a specific location throughout a given period.

Displayed as circular bar charts, wind roses use changes in position and color to show changes.. They include descriptive captions and help sailors, architects, or meteorologists in decision-making processes.

The example featured includes a detailed wind rose covering 24 hours. You can effortlessly identify the changes throughout the day. This dynamic visualization shows how simple graphs aid research and display vital data.

Economic Dynamic Visualizations

Big Mac Index

The Big Mac Index is a measurement that evaluates consumer purchase power and market exchange rates. It centers its comparison on the value of a McDonald’s Big Mac burger in different countries.

Using the US dollar as a base value, the dynamic visualizations allow you to see the value for each country on a given date. Then, that value is correlated to the Gross Domestic Product per individual.

The interactive map above shows data from each country and follows its evolution from 2000 to 2022. With this graph, users understand the relationship between major events and currency value in each country.

Other Data Visualization Examples

Deviation Dashboard

The Deviation Dashboard is one of the most valuable tools to display multiple variables in a single data visualization. These bar charts generate an overview of standard deviations that value below or above their sample means.

The deviation dashboard is a dynamic data visualization that also includes color variations. Variables that reach 1-sigma are in dark green, 1 to 2-sigma in light green, 2 to 3-sigma in yellow, and above 3-sigma in red.

This visual data approach is more suited to processing complex data. It helps analyze relationships between extreme events and the values generated.

The example, in this case, features an in-motion data visualization of deviation boards comprising 40 years. It depicts the fish counts of 13 distinct locations within the Gulf of Maine region.

Nebulous; idea not connected to a point.